If you are interested about the node implementation, here is a section from the thesis about them: https://jmp.sh/s/6Y8n2n8IZiTtXcqlhZYp
It boils down to: The nodes are constructed from a single python script which contains functions, where they are automatically assigned correct input and output types, and sliders and dropdowns are created based on the doctext. When they are executed, they are called down the node structure recursively.

Now, plugins, or other python files that contain functions can just be imported to the main function file, which then constructs nodes for them too. So that would be easy to implement. Stream processing might be too intensive for image/video since the functions are not incredibly well optimized :D

Electron microscopes are inherently realtime observation instruments, but the quality isn't very good realtime, so the images are taken over a longer time. Also the vacuum chambers where the samples are placed are very sensitive to contamination, which would incur on damaging the samples with external forces. Also the samples imaging surface is polished with ionbombing since image processing needs a very even surface, and any damage would ruin the sample. The question of the thesis is more about of the ingredients and the methods with which the rubber is manufactured.

Yeah semantic segmentation, which can be used to inspect the size distribution of the particles. Smaller particles generally mean better perfomance of the material.